Training in progress epoch 5

README.md

@@ -15,17 +15,17 @@ probably proofread and complete it, then remove this comment. -->
 
 This model is a fine-tuned version of [bert-large-uncased](https://huggingface.co/bert-large-uncased) on an unknown dataset.
 It achieves the following results on the evaluation set:
-- Train Loss: 0.1614
-- Train Accuracy: 0.9404
-- Train F1 M: 0.5316
-- Train Precision M: 0.3944
-- Train Recall M: 0.8756
-- Validation Loss: 0.2188
-- Validation Accuracy: 0.9235
-- Validation F1 M: 0.5566
-- Validation Precision M: 0.4080
-- Validation Recall M: 0.9242
-- Epoch: 4
+- Train Loss: 0.1380
+- Train Accuracy: 0.9497
+- Train F1 M: 0.5359
+- Train Precision M: 0.3956
+- Train Recall M: 0.8898
+- Validation Loss: 0.2205
+- Validation Accuracy: 0.9228
+- Validation F1 M: 0.5506
+- Validation Precision M: 0.4024
+- Validation Recall M: 0.9213
+- Epoch: 5
 
 ## Model description
 
@@ -56,6 +56,7 @@ The following hyperparameters were used during training:
 | 0.2254     | 0.9128         | 0.5069     | 0.3838            | 0.8028         | 0.2388          | 0.9090              | 0.5468          | 0.4009                 | 0.9053              | 2     |
 | 0.1873     | 0.9303         | 0.5203     | 0.3889            | 0.8490         | 0.2200          | 0.9149              | 0.5561          | 0.4075                 | 0.9235              | 3     |
 | 0.1614     | 0.9404         | 0.5316     | 0.3944            | 0.8756         | 0.2188          | 0.9235              | 0.5566          | 0.4080                 | 0.9242              | 4     |
+| 0.1380     | 0.9497         | 0.5359     | 0.3956            | 0.8898         | 0.2205          | 0.9228              | 0.5506          | 0.4024                 | 0.9213              | 5     |
 
 
 ### Framework versions

tf_model.h5

@@ -1,3 +1,3 @@
 version https://git-lfs.github.com/spec/v1
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+oid sha256:7d27c82601705cec272732dd076f3c99c4dbba525062b8944172f392e4473935
 size 1341127728